Topic models have recently emerged as powerful tools for modeling topical trends in documents. Often the resulting topics are broad and generic, associating large groups of people...
Vidit Jain, Erik G. Learned-Miller, Andrew McCallu...
Abstract. Machine learning approaches in natural language processing often require a large annotated corpus. We present a complementary approach that utilizes expert knowledge to o...
In this paper we propose a data intensive approach for inferring sentence-internal temporal relations. Temporal inference is relevant for practical NLP applications which either e...
The exponential growth and reliability of Wikipedia have made it a promising data source for intelligent systems. The first challenge of Wikipedia is to make the encyclopedia mac...
Weaddress the problemof generalizing temporal data concerning durations extracted from relational databases.Ourapproachisbasedona domaingenerMizationgraphthatdefinesa partialorder...
Dee Jay Randall, Howard J. Hamilton, Robert J. Hil...